LLM Training Operation Specialist - Seed Global Data

LLM Training Operation Specialist - Seed Global Data

Location:

Team:

User ops

Employment Type:

Regular

Job Code:

A131331

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About the team

Seed Global Data is a team focused on producing international data for LLMs. For the training of large models, data is the lifeline of model quality — and the Global Data team is working closely with technical, product, and operations teams to ensure effective data production strategies and execution management.

As a key member of Seed Global Data team, you'll be at the heart of our operations. This role focuses on advanced evaluation, training, and project execution related to annotating/training Large Language Models (LLMs) with diverse data sets. You will leverage your expertise to devise complex projects and contribute to strategic decisions that drive our data operations and research forward.

Key

Responsibilities and Duties:

• Evaluation Work:
  Conduct comprehensive analysis and evaluation of AI models. Apply advanced knowledge and judgment to assess model performance and develop insights. Mentor and guide internal colleagues and external partners on specific topics, ensuring the quality and relevance of the evaluation process.
• Reporting:
  Write detailed reports that document and communicate findings from evaluation work. Develop specialized skills in our data and content domain, and use this expertise to enhance the quality and depth of model training and evaluation outputs.
• Documentation and Project Support:
  Draft and manage training guidelines and casebooks for specific projects and tasks. Support project coordination, offering flexible availability to accommodate discussion meetings with global teams.
• Project Execution:
  Deliver high-quality annotation work to create SFT and RLHF data independently with limited supervision. Ensure that all project tasks are executed with a strong focus on quality and efficiency and take ownership of casebooks and guideline updates for scaled annotation.

Minimum Qualifications:

• Advanced proficiency in English with exceptional writing and analytical skills.
• Comfortable working in a project-based, fast-paced environment, adaptable to rapidly evolving quality standards driven by research and experimentation.
• Strong ability to exercise independent judgment and discretion while effectively contributing to a highly collaborative team.
• Broad exposure to AI tools and platforms; comfortable working in spreadsheet applications.

Preferred Qualifications:

• Over 2 years of experience in research, consulting, teaching, writing, or equivalent roles. Prior experience in RLHF annotation at AI/LLM companies strongly preferred.
• Proven self-driven work ethic and demonstrated ability to lead and mentor junior team members in process and project execution.
• Deep interest in LLMs, human behavior, and user experience, coupled with a strong enthusiasm for continuous learning and engaging with diverse case studies and global teams.
• Strong working proficiency in AI platforms and Python automation (scripts/notebooks, APIs), enabling faster, more reliable data workflows across evaluation/training and research.

Note:

This role requires a test prior to interviews.

The hourly rate range for this position in the selected city is $33.70- $56.03.

Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.

Benefits may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).

The Company…